Difference between revisions of "CHEM-6111"

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(Introduction to computer graphing, functions and programming (Igor, 2 weeks))
(Basic Data Analysis (Igor, 6 weeks))
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** weighted vs unweighted regression
 
** weighted vs unweighted regression
 
* boxcar and weighted smoothing
 
* boxcar and weighted smoothing
 +
** propagation of errors
 
* Signal-to-noise, noise reducing measures, signal enhancing measures, numerical high pass filters, low pass filters etc.
 
* Signal-to-noise, noise reducing measures, signal enhancing measures, numerical high pass filters, low pass filters etc.
 
* Fitting of custom functions
 
* Fitting of custom functions

Revision as of 12:27, 20 August 2012

CHEM 6111 - Special Topics - Data Analysis and Acquisition

This 3-credit course will be offered by Dr. Ingrid Ulbrich (with assistance from Prof. Jose L. Jimenez) in Fall of 2012. It will be a required course for 1st year analytical chemistry students, and optional for others.


Course Information

  • Lectures: Tue & Thur 12:30 pm - 1:45 pm, Ekeley W166
  • Office Hours: TBD
  • Required Texts
    • Taylor, Error Analysis, 2nd. Ed., 1997. ISBN: 093570275X, on reserve at Norlin
    • Press, Teukolsky, Vetterling, and Flannery, Numerical Recipes
    • Allen and Tildesley, Computer Simulation of Liquids, 1987. Selections will be posted here.

Lectures, Reading, and Homework

Introduction to computer graphing, functions and programming (Igor, 2 weeks)

Basic Data Analysis (Igor, 6 weeks)

  • propagation of errors
  • Basic analysis: interpolation, area integrals, multidimensional data handling
  • Statistics: calculating statistical parameters, distributions, precision, uncertainty, ANOVAA
  • Correlation and regressions (variants)
    • centered (Pearson's) vs uncentered correlation
    • vertical vs orthogonal distance regression
    • squared vs absolute value errors for regression
    • weighted vs unweighted regression
  • boxcar and weighted smoothing
    • propagation of errors
  • Signal-to-noise, noise reducing measures, signal enhancing measures, numerical high pass filters, low pass filters etc.
  • Fitting of custom functions

Advanced Data Analysis (Igor, 4 weeks)

  • Numerical solution of ODEs
  • convolution (student request to IMU)
  • Montecarlo simulations
  • Positive Matrix Factorization
  • Frequency analysis and FFT

Data Acquisition (Labview, 3 weeks)

  • Fundamentals of data acquisition
  • Data I/O, parsing of text files, write to file etc.
  • Labview: introduction and programming
  • Data acquisition problems brought by students from their research

Additional Resources

  • Additional Texts
    • Building Scientific Apparatus (Moore, Davis, and Coplan)